Modeling of a non-relational database as a relational database

ABSTRACT

A system and method are disclosed for modeling a non-relational database as a normalized relational database. In one embodiment, the system identifies a column having a first type in a column-oriented, non-relational database; determines whether the column-oriented, non-relational database includes at least one column having a second type and identifies the one or more columns having the second type; virtually divides the column-oriented, non-relational database based on column type; and generates a normalized, relational model based on the virtual division of the column-oriented, non-relational database, the normalized, relational model including catalog information representing a parent table including the column having the first type and, when the column-oriented, non-relational database includes at least one column having the second type, catalog information representing a child table, the parent table and child table both represented as relational tables.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/074,549, entitled “Modeling of a Non-Relational Database as aNormalized Relational Database,” filed on Nov. 7, 2013, the entirety ofwhich is herein incorporated by reference.

Applicants hereby notify the USPTO that the claims of the presentapplication are different from those of the parent application and anyother related applications. Therefore, Applicants rescind any disclaimerof claim scope made in the parent application or any other predecessorapplication in relation to the present application. The Examiner istherefore advised that any such disclaimer and the cited reference thatit was made to avoid may need to be revisited at this time. Furthermore,the Examiner is also reminded that any disclaimer made in the presentapplication should not be read into or against the parent application orany other related application.

FIELD OF INVENTION

The present disclosure relates to modeling a non-relational database asa relational database. More specifically, the present disclosure relatesto modeling a non-relational database as a normalized relationaldatabase.

BACKGROUND

Common drivers may use relational database query languages. For example,Open Database Connectivity (ODBC) and Java Database Connectivity (JDBC)drivers use Structured Query Language (SQL) as a query language.Relational database systems may normalize data by dividing data tablesinto smaller tables that are less redundant. For example, the relationaltable 900 of FIG. 9, when normalized, may be divided into table 1000 andtable 1002 of FIG. 10. These smaller tables have relationships betweenthem so that the original de-normalized data table 900 may bereconstructed. The objective of normalization is to reduce redundanciesand ideally isolate data so that additions, deletions and modificationsto a field may be made in just one table and propagated through thedatabase using the defined relationships. In a relational model,different rows in the same table share the same set of columns.Non-relational databases do not follow the relational model. Forexample, Cassandra, a Not Only SQL (NoSQL) database, stores related datathat is commonly accessed in the same row and different rows do notnecessarily share the same set of columns. Therefore, Cassandra is anon-relational database.

Current methods and systems fail to adapt a non-relational data model toappear as a relational data model, which would allow standard driverslike ODBC and JDBC drivers to access the data stored in thenon-relational model and make the data tables appear as if stored in arelational database to an application using the driver.

SUMMARY

In general, an innovative aspect of the subject matter described in thisdisclosure may be embodied in methods that include identifying, usingone or more processors, a column having a first type in acolumn-oriented, non-relational database; determining, using one or moreprocessors, whether the column-oriented, non-relational databaseincludes at least one column having a second type; responsive todetermining that column-oriented, non-relational database includes atleast one column having the second type, identifying, using one or moreprocessors, the one or more columns having the second type; virtuallydividing, using one or more processors, the column-oriented,non-relational database based on column type; and generating, using oneor more processors, a normalized, relational model of thecolumn-oriented, non-relational database based on the virtual divisionof the column-oriented, non-relational database, the normalized,relational model including catalog information representing a parenttable including the column having the first type and, when thecolumn-oriented, non-relational database includes at least one columnhaving the second type, catalogue information representing a childtable, the parent table and child table both represented as relationaltables.

According to one another innovative aspect of the subject matterdescribed in this disclosure, a system comprises a processor; and amemory storing instructions that, when executed, cause the system to:identify a column having a first type in a column-oriented,non-relational database; determine whether the column-oriented,non-relational database includes at least one column having a secondtype; responsive to determining that column-oriented, non-relationaldatabase includes at least one column having the second type,identifying, using one or more processors, the one or more columnshaving the second type; virtually divide the column-oriented,non-relational database based on column type; and generate a normalized,relational model of the column-oriented, non-relational database basedon the virtual division of the column-oriented, non-relational database,the normalized, relational model including catalog informationrepresenting a parent table including the column having the first typeand, when the column-oriented, non-relational database includes at leastone column having the second type, catalogue information representing achild table, the parent table and child table both represented asrelational tables.

Other implementations of one or more of these aspects includecorresponding systems, apparatus, and computer programs, configured toperform the actions of the methods, encoded on computer storage devices.These and other implementations may each optionally include one or moreof the following features.

For instance, the catalogue information representing the parent tableincludes each column in the column-oriented, non-relational databasehaving the first type. For instance, the column-oriented, non-relationaldatabase is a Cassandra database and uses Cassandra Query Languageversion 2. For instance, the column-oriented, non-relational database isa Cassandra database and uses Cassandra Query Language version 3. Forinstance, the one or more identified columns having the second type arerepresented as a separate child table in the normalized, relationalmodel. For instance, the non-relational database table includes aplurality of columns having the second type and the relation modelincludes catalogue information representing at least two child tablesincluding a first child table including a first set of the plurality ofcolumns having the second type and a second child table including asecond set of the plurality of columns having the second type. Forinstance, the operations further include receiving a relational queryfrom a driver; retrieving the normalized, relational model of thecolumn-oriented, non-relational database; mapping the relational queryto associated fields and query language for the column-oriented,non-relational database using the normalized, relational model of thecolumn-oriented, non-relational database; generating a non-relationalquery; and sending the non-relational query to the column-oriented,non-relational database. For instance, the driver is one of a JavaDatabase Connectivity driver and an Open Database Connectivity driver.For instance, the operations further include receiving a non-relationalresponse from the column-oriented, non-relational database; retrievingthe normalized, relational model of the column-oriented, non-relationaldatabase; mapping the non-relational response to associated fields andquery language for the a driver that uses a relational query languageusing the normalized, relational model of the column-oriented,non-relational database; generating a relational response; and sendingthe relational response to the driver that uses the relational language.

It should be understood that this list of features and advantages is notall-inclusive and many additional features and advantages arecontemplated and fall within the scope of the present disclosure.Moreover, it should be understood that the language used in the presentdisclosure has been principally selected for readability andinstructional purposes, and not to limit the scope of the subject matterdisclosed herein.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure is illustrated by way of example, and not by way oflimitation in the figures of the accompanying drawings in which likereference numerals are used to refer to similar elements.

FIG. 1 is a block diagram illustrating an example system for modeling anon-relational database as a normalized relational database according toone embodiment.

FIG. 2 is a block diagram illustrating an example computing deviceaccording to one embodiment.

FIG. 3 is a block diagram of a model generation module according to oneembodiment.

FIG. 4 is a block diagram of a relational/non-relational translatormodule according to one embodiment.

FIG. 5 is a flowchart of an example method for generating a model of anon-relational database as a normalized relational database according toone embodiment.

FIG. 6 is a flowchart of an example method using a model of anon-relational database as a normalized relational database according toone embodiment.

FIG. 7 is an example of a non-relational database table according to oneembodiment.

FIG. 8 is an example of how data from a non-relational database tablemay be organized as one or more normalized relational database tablesaccording to one embodiment.

FIG. 9 is an example of a de-normalized, relational database tableaccording to one embodiment.

FIG. 10 is an example of normalized, relational database tablesaccording to one embodiment.

DETAILED DESCRIPTION

FIG. 1 is a block diagram illustrating an example system 100 formodeling a non-relational database as a normalized relational databaseaccording to one embodiment. The illustrated system 100 includes clientdevices 106 a . . . 106 n, a non-relational database 120 and an optionalconnectivity server 122, which are communicatively coupled via a network102 for interaction with one another. For example, the client devices106 a . . . 106 n (also referred to individually and collectively as106) may be respectively coupled to the network 102 via signal lines 104a . . . 104 n and may be accessed by users 112 a . . . 112 n (alsoreferred to individually and collectively as user 112) as illustrated bylines 110 a . . . 110 n. The non-relational database 120 may be coupledto the network 102 via signal line 114. The optional connectivity server122 may be coupled to the network 102 via signal line 120. The use ofthe nomenclature “a” and “n” in the reference numbers indicates that anynumber of those elements having that nomenclature may be included in thesystem 100.

The network 102 may include any number of networks and/or network types.For example, the network 102 may include, but is not limited to, one ormore local area networks (LANs), wide area networks (WANs) (e.g., theInternet), virtual private networks (VPNs), mobile networks (e.g., thecellular network), wireless wide area network (WWANs), Wi-Fi networks,WiMAX® networks, Bluetooth® communication networks, peer-to-peernetworks, other interconnected data paths across which multiple devicesmay communicate, various combinations thereof, etc. Data transmitted bythe network 102 may include packetized data (e.g., Internet Protocol(IP) data packets) that is routed to designated computing devicescoupled to the network 102. In some implementations, the network 102 mayinclude a combination of wired and wireless (e.g., terrestrial orsatellite-based transceivers) networking software and/or hardware thatinterconnects the computing devices of the system 100. For example, thenetwork 102 may include packet-switching devices that route the datapackets to the various computing devices based on information includedin a header of the data packets.

The data exchanged over the network 102 can be represented usingtechnologies and/or formats including the hypertext markup language(HTML), the extensible markup language (XML), JavaScript Object Notation(JSON), Comma Separated Values (CSV), etc. In addition, all or some oflinks can be encrypted using conventional encryption technologies, forexample, the secure sockets layer (SSL), Secure HTTP (HTTPS) and/orvirtual private networks (VPNs) or Internet Protocol security (IPsec).In another embodiment, the entities can use custom and/or dedicated datacommunications technologies instead of, or in addition to, the onesdescribed above. Depending upon the embodiment, the network 102 can alsoinclude links to other networks.

The client devices 106 are computing devices having data processing andcommunication capabilities. While FIG. 1 illustrates two client devices106, the present specification applies to any system architecture havingone or more client devices 106. In some embodiments, a client device 106may include a processor (e.g., virtual, physical, etc.), a memory, apower source, a network interface, and may include other componentswhether software or hardware, such as a display, graphics processor,wireless transceivers, keyboard, camera, sensors, firmware, operatingsystems, drivers, various physical connection interfaces (e.g., USB,HDMI, etc.). The client devices 106 a . . . 106 n may couple to andcommunicate with one another and the other entities of the system 100via the network 102 using a wireless and/or wired connection.

Examples of client devices 106 may include, but are not limited to,mobile phones (e.g., feature phones, smart phones, etc.), tablets,laptops, desktops, netbooks, server appliances, servers, virtualmachines, TVs, set-top boxes, media streaming devices, portable mediaplayers, navigation devices, personal digital assistants, etc. While twoor more client devices 106 are depicted in FIG. 1, the system 100 mayinclude any number of client devices 106. In addition, the clientdevices 106 a . . . 106 n may be the same or different types ofcomputing devices. In the depicted implementation, the client devices106 a . . . 106 n respectively contain instances 109 a . . . 109 n of adriver 109.

The driver 109 may be storable in a memory and executable by a processorof a client device 106. In some embodiments, the client device 106includes one or more applications (not shown) that use the driver 109.For example, the client device 106 includes an application (not shown)that uses driver 109 to access data in the non-relational database 120.

The optional connectivity server 122 may include one or more computingdevices having data processing, storing, and communication capabilities.For example, the connectivity server 122 may include one or morehardware servers, server arrays, storage devices, systems, etc., and/ormay be centralized or distributed/cloud-based. In some implementations,the connectivity server 122 may include one or more virtual servers,which operate in a host server environment and access the physicalhardware of the host server including, for example, a processor, memory,storage, network interfaces, etc., via an abstraction layer (e.g., avirtual machine manager).

In one embodiment, the connectivity server 122 includes an instance ofthe driver 109 x. For example, in one embodiment, a relational languagebased driver (e.g. a JDBC driver, an ODBC driver or any other driverthat uses a relational query language) (not shown) of a client device106 may send relational queries to the connectivity server 122 in arelational database language (e.g. SQL) and the driver 109 x of theconnectivity server 122 generates a relational model of thenon-relational database 120 and translates the query for thenon-relational database 120 and translates the response from thenon-relational database 120 into the relational database language usedby the relational language based driver (not shown). Such an embodimentmay beneficially provide connectivity to a non-relational database as aweb service using drivers designed for relational databases. In oneembodiment, the connectivity server 122 provides client devices 106 andtheir applications (not shown) connectivity to a variety of hardware andservices without the client device 106 including additional drivers. Forexample, connectivity server 122 may host driver 109 x for exposing datastored in a non-relational database 120 as well as other drivers (notshown) that may expose an application (not shown) to other hardwareand/or services using a JDBC or ODBC driver (not shown) on the clientdevice 106.

The non-relational database 122 may include one or more non-transitorycomputer-readable mediums for storing data. While the illustratednon-relational database 122 is illustrated as connected to the network102 via signal line 114, in some embodiments, the non-relationaldatabase 120 may be included in a memory or storage device (e.g. a harddisk drive) of the client device 106 or connected to (e.g. as a DirectAccess Storage) a client device 106. In one embodiment, thenon-relational database 120 includes a database management system(DBMS). For example, the DBMS may be a non-relational DBMS, for example,a NoSQL DMBS. In some instances, the DBMS may store data inmulti-dimensional tables comprised of rows and columns, and manipulate,i.e., insert, query, update and/or delete, rows of data usingprogrammatic operations. While only one relational database 120 isillustrated, it will be recognized that multiple non-relationaldatabases 120 may exist. For example, in one embodiment, thenon-relational database 120 is a distributed database.

In one embodiment, the non-relational database 120 is a NoSQL database.In one embodiment, the non-relational database 120 is a column-orientedNoSQL database. For example, in one embodiment, the non-relationaldatabase is a Cassandra database. For clarity and convenience, Cassandrais referred to and used in many of the examples herein. However, it willbe recognized that Cassandra is merely one example of a column-oriented,non-relational database and that other examples exist and may be usedwithout departing from the disclosure herein.

It should be understood that the system 100 illustrated in FIG. 1 isrepresentative of an example system for modeling a non-relationaldatabase as a normalized relational database according to one embodimentand that a variety of different system environments and configurationsare contemplated and are within the scope of the present disclosure. Forinstance, various functionality may be moved from a server to a client,or vice versa and some implementations may include additional or fewercomputing devices, services, and/or networks, and may implement variousfunctionality client or server-side. Further, various entities of thesystem 100 may be integrated into to a single computing device or systemor additional computing devices or systems, etc.

FIG. 2 is a block diagram of an example computing device 106/122according to one embodiment. The computing device 106/122, asillustrated, may include a processor 202, a memory 204 and acommunication unit 208, which may be communicatively coupled by acommunications bus 206. The computing device 106/122 depicted in FIG. 2is provided by way of example and it should be understood that it maytake other forms and include additional or fewer components withoutdeparting from the scope of the present disclosure. For example, whilenot shown, the computing device 106/122 may include a storage device,input and output devices (e.g., a display, a keyboard, a mouse, touchscreen, speakers, etc.), various operating systems, sensors, additionalprocessors, and other physical configurations. Additionally, it shouldbe understood that the computer architecture depicted in FIG. 2 anddescribed herein may be applied to multiple entities in a system 100,for example, the computing device 106/122 may be a client device 106 ora connectivity server 122.

The processor 202 may execute code, routines and software instructionsby performing various input/output, logical, and/or mathematicaloperations. The processor 202 have various computing architectures toprocess data signals including, for example, a complex instruction setcomputer (CISC) architecture, a reduced instruction set computer (RISC)architecture, and/or an architecture implementing a combination ofinstruction sets. The processor 202 may be physical and/or virtual, andmay include a single core or plurality of processing units and/or cores.In some implementations, the processor 202 may be capable of generatingand providing electronic display signals to a display device (notshown), supporting the display of images, capturing and transmittingimages, performing complex tasks including various types of featureextraction and sampling, etc. In some implementations, the processor 202may be coupled to the memory 204 via the bus 206 to access data andinstructions therefrom and store data therein. The bus 206 may couplethe processor 202 to the other components of the computing device106/122 including, for example, the memory 204 and communication unit208.

The memory 204 may store and provide access to data to the othercomponents of the computing device 106/122. In some implementations, thememory 204 may store instructions and/or data that may be executed bythe processor 202. For example, in the illustrated embodiment, thememory 204 may store the driver 109. The memory 204 is also capable ofstoring other instructions and data, including, for example, anoperating system, hardware drivers, other software applications,databases, etc. The memory 204 may be coupled to the bus 206 forcommunication with the processor 202 and the other components of thecomputing device 106/122.

In the illustrated embodiment, the driver 109 includes a modelgeneration module 224, a relational/non-relational translator module 226and a relational model 228. In one embodiment, the model generationmodule 224 generates the relational model 228, and therelational/non-relational translator module 226 uses the relationalmodel 228 to translate relational queries into non-relational queriesand non-relational responses into relational responses. For example, inone embodiment, the model generation module 224 generates a normalized,relational model of a Cassandra table, the relational/non-relationaltranslator module 226, upon receiving a SQL query from a JDBC or ODBCdriver, obtains the normalized, relational model and translates the SQLquery into a Cassandra Query Language (CQL) query and sends the CQLquery to the Cassandra database. The Cassandra database returns aresponse using CQL, which the relational/non-relational translatormodule 226 receives and translates, using the normalized, relationalmodel, into a SQL response, which is returned to the JDBC or ODBCdriver.

In one embodiment, the driver 109 includes a relational language baseddriver (not shown). For example, in one embodiment, the driver 109 ofthe client device 106 includes one or more of a JDBC driver (not shown)and an ODBC driver (not shown) which may be included as a layer withinthe driver 109 of the client device 106. For example, the driver 109includes a JDBC or ODBC driver layer that receives requests from anapplication (not shown), passes relational queries to therelational/non-relational translator module 226 based on the requests,receives a relational response from the relational/non-relationaltranslator module 226 and returns a response to the application (notshown).

The memory 204 includes a non-transitory computer-usable (e.g.,readable, writeable, etc.) medium, which can be any apparatus or devicethat can contain, store, communicate, propagate or transportinstructions, data, computer programs, software, code, routines, etc.,for processing by or in connection with the processor 202. In someimplementations, the memory 204 may include one or more of volatilememory and non-volatile memory. For example, the memory 204 may include,but is not limited, to one or more of a dynamic random access memory(DRAM) device, a static random access memory (SRAM) device, a discretememory device (e.g., a PROM, FPROM, ROM), a hard disk drive, an opticaldisk drive (CD, DVD, Blue-Ray™, etc.). It should be understood that thememory 204 may be a single device or may include multiple types ofdevices and configurations.

The bus 206 can include a communication bus for transferring databetween components of a computing device 106/122 and/or betweencomputing devices (e.g. between one or more of the client device 106,connectivity server 122 and non-relational database 120), a network bussystem including the network 102 or portions thereof, a processor mesh,a combination thereof, etc. In some implementations, the driver 109, itssub-components 224, 226, 228, their subcomponents 322, 324, 326, 328,330, 422, 424 and various other software operating on the computingdevice 106/122 (e.g., an operating system, etc.) may cooperate andcommunicate via a software communication mechanism implemented inassociation with the bus 206. The software communication mechanism caninclude and/or facilitate, for example, inter-process communication,local function or procedure calls, remote procedure calls, an objectbroker (e.g., CORBA), direct socket communication (e.g., TCP/IP sockets)among software modules, UDP broadcasts and receipts, HTTP connections,etc. Further, any or all of the communication could be secure (e.g.,SSH, HTTPS, etc.).

The communication unit 208 may include one or more interface devices(I/F) for wired and/or wireless connectivity with the network 102. Forinstance, the communication unit 208 may include, but is not limited to,CAT-type interfaces; wireless transceivers for sending and receivingsignals using radio transceivers (4G, 3G, 2G, etc.) for communicationwith the mobile network 102, and radio transceivers for Wi-Fi™ andclose-proximity (e.g., Bluetooth®, NFC, etc.) connectivity, etc.; USBinterfaces; various combinations thereof; etc. In some implementations,the communication unit 208 can link the processor 202 to the network102, which may in turn be coupled to other processing systems. Thecommunication unit 208 can provide other connections to the network 102and to other entities of the system 100 using various standard networkcommunication protocols.

As mentioned above, the computing device 106/122 may include otherand/or fewer components. Examples of other components may include adisplay, an input device, a sensor, etc. (not shown). In one embodiment,the computing device 106/122 includes a display. The display may displayelectronic images and data for presentation to a user 112. The displaymay include any conventional display device, monitor or screen,including, for example, an organic light-emitting diode (OLED) display,a liquid crystal display (LCD), etc. In some implementations, thedisplay may be a touch-screen display capable of receiving input from astylus, one or more fingers of a user 112, etc. For example, the displaymay be a capacitive touch-screen display capable of detecting andinterpreting multiple points of contact with the display surface.

The input device (not shown) may include any device for inputtinginformation into the computing device 106/122. In some implementations,the input device may include one or more peripheral devices. Forexample, the input device may include a keyboard (e.g., a QWERTYkeyboard or keyboard in any other language), a pointing device (e.g., amouse or touchpad), microphone, an image/video capture device (e.g.,camera), etc. In some implementations, the input device may include atouch-screen display capable of receiving input from the one or morefingers of the user 112. For example, the user 112 could interact withan emulated (i.e., virtual or soft) keyboard displayed on thetouch-screen display by using fingers to contacting the display in thekeyboard regions.

Example Virtual Model Generation Module 224

Referring now to FIG. 3, the model generation module 224 is shown inmore detail according to one embodiment. FIG. 3 is a block diagram ofthe model generation module 224 included in a computing device 106/122according to one embodiment.

The model generation module 224 generates a relational model 228 of anon-relational database 120, which may be used by therelational/non-relational translator module 226 to expose the data inthe non-relational database 120 to access by drivers using a relationalquery language. For clarity and convenience, an example of anon-relational database table 700 is provided in FIG. 7 and thefunctionality of the model generation module 224 and its subcomponents322, 324, 326, 328, 330 are discussed with reference to non-relationaldatabase table 700. In one embodiment, the non-relational database table700 is a column-oriented, non-relational database table (e.g. usingCassandra). It should be recognized that non-relational database table700 is merely one example of a non-relational database table and othersexist.

Depending on the embodiment, the model generation module 224 maygenerate the relational model responsive to one or more of anestablishment of a connection with the non-relational database 120, aschema modifying update and the expiration of a period. For example, inone embodiment, the model generation module 224 generates the relationalmodel 228 responsive to the driver 109 connecting to the non-relationaldatabase 120. In another example, in one embodiment, the modelgeneration module 224 generates the relational model 228 responsive toreceiving a schema modifying update. A schema modifying request is arequest that modifies the non-relational database 120 in a manner thataffects the relational model 228. For example, in one embodiment, themodel generation module 228 generates a relational model 228 responsiveto determining that a column has been added/removed from thenon-relational database 120. In yet another example, in one embodiment,the model generation module 224 generates the relational model 228periodically (e.g. every X units of time, every Y queries, every Z typeof query, etc.). Such embodiments may ensure that the relational modelremains current and reflects updates to the non-relational database 120.

In one embodiment, the non-relational database 120 is a column-orienteddatabase. In some embodiments, a column-oriented, non-relationaldatabase may have multiple column types. For example, thecolumn-oriented non-relational database may have one or more columns ofa first type that are more relational in nature (e.g. shared by allrows) and zero or more columns of a second type that are not relationalin nature. The first type of column (i.e. the column type that is morerelational in nature) is occasionally referred to herein as a staticcolumn. The second type of column (i.e. the column type that is notrelational in nature) is occasionally referred to herein as a dynamiccolumn.

In one embodiment, the model generation module 224 comprises a staticcolumn determination module 322, a dynamic column determination module324, an optional dynamic column typing module 326, a table divisionmodule 328 and a modeling module 330. It will be recognized that themodules 322, 324, 326, 328, 330 comprised in the model generation module224 are not necessarily all on the same computing device 106/122. In oneembodiment, the modules 322, 324, 326, 328, 330 and/or theirfunctionality are distributed across multiple computing devices 106/122.For example, in one embodiment, the modules 322, 324, 326, 328, 330, 332are distributed across multiple connectivity servers 122.

The static column determination module 322 includes code and routinesfor identifying a static column in the non-relational database table. Inone embodiment, the static column determination module 322 is a set ofinstructions executable by the processor 202. In another embodiment, thestatic column determination module 322 is stored in the memory 204 andis accessible and executable by the processor 202. In either embodiment,the static column determination module 322 is adapted for cooperationand communication with the processor 202, other components of thecomputing device 106/122 and other components of the model generationmodule 224.

The static column determination module 322 identifies static columns inthe non-relational database table. In some embodiments, a static columnincludes a column that is shared by all rows in the table and is,therefore, relational in nature. For example, the column that includes akey for each row in the non-relational database table is a staticcolumn. In one embodiment, a static column may be shared by all rows inthe table, but each row is not required to have the column defined. Inone embodiment, a static column is a static column as defined byCassandra. In one embodiment, a non-relational database 120 includes atleast one static column. For example, in one embodiment, anon-relational database includes a column for a key for each row in thenon-relational database table and that key column is a static column.

In one embodiment, the static column determination module 322 identifiesstatic columns in the non-relational database table explicitly. In oneembodiment, the static column determination module 322 identifies staticcolumns in the non-relational database table explicitly using thedefinition of the non-relational database table. For example, referringto FIG. 7, assume that table 700 is titled MusicCDs, in one embodiment,the static columns 702 are defined upon creation of the table to be theKey 716, CD 718, Artist 720 and Year 722 columns. For example, using CQLversion 2, assume the MusicCDs table 700 is created using the command“CREATE TABLE MusicCDs (UUID PRIMARY KEY, CD varchar, Artist varchar,Year int);” in one embodiment, the static column determination module322 determines that KEY, CD, Artist and Year are the static columns oftable 700 from this definition. In another example, using CQL version 3,assume the MusicCDs table 700 is created using the command “CREATE TABLEMusicCDs (UUID PRIMARY KEY, CD varchar, Artist varchar, Year int, Songsmap<varchar, varchar>);” in one embodiment, the static columndetermination module 322 determines that KEY, CD, Artist and Year arethe static columns of table 700 from this definition.

In one embodiment, the static column determination module 322 identifiesstatic columns in the non-relational database table implicitly. Examplesof implicit determination include but are not limited to determinationbased on the organization and location of the columns (e.g. left mostcolumns may be more likely to be static columns), based on how many rowsshare the column (e.g. whether all or nearly all rows define thecolumn), etc.

Referring again to FIG. 3, in one embodiment, the static columndetermination module 322 passes the identity of the static columns tothe table division module 328. In one embodiment, the static columndetermination module 322 stores the information identifying theidentified static columns in memory 204 (or any other non-transitorystorage medium communicatively accessible). The other modules of themodel generation module 224 including, e.g., the table division module328, may retrieve the identity of the static columns from the memory 204(or other non-transitory storage medium).

The dynamic column determination module 324 includes code and routinesfor identifying a dynamic column in a non-relational database. In oneembodiment, the dynamic column determination module 324 is a set ofinstructions executable by the processor 202. In another embodiment, thedynamic column determination module 324 is stored in the memory 204 andis accessible and executable by the processor 202. In either embodiment,the dynamic column determination module 324 is adapted for cooperationand communication with the processor 202, other components of thecomputing device 106/122 and other components of the model generationmodule 224.

The dynamic column determination module 324 identifies dynamic columnsin the non-relational database table. In one embodiment, a dynamiccolumn is a column that is not relational in nature. For example adynamic column that is not shared by all rows. For example, referring,again, to table 700 of FIG. 7, the column for “Song E” 712 is definedfor the first row 708, but not for the second row 710. In oneembodiment, a dynamic column is a dynamic column as defined byCassandra.

In one embodiment, a non-relational database table may include zero ormore dynamic columns. In other words, in some embodiments, anon-relational database table does not necessarily include a dynamiccolumn. In one embodiment, the dynamic column determination module 324determines whether the non-relational database table includes one ormore dynamic columns.

In one embodiment, the dynamic column determination module 324determines whether at least one dynamic column exists by comparing thecolumns in the non-relational table to that table's definition. Forexample, as described above with reference to FIG. 7, the MusicCDs tablemay be created using a CQL version 2 command “CREATE TABLE MusicCDs(UUID PRIMARY KEY, CD varchar, Artist varchar, Year int);” and, in oneembodiment, the dynamic column determination module 324 may compare thecolumns of table 700 to the columns defined in table creation anddetermine that dynamic columns 704 are present in table 700. Forexample, the dynamic column determination module 324 determines whethercolumns exist in table 700 that were not defined at table creationbecause CQL versions 2 and 3 permit the addition and removal of dynamiccolumns as needed without such definition.

In one embodiment, the dynamic column determination module 324determines whether at least one dynamic column exists by analyzing thetable definition for inclusion of a dynamic column type. For example, asdescribed above with reference to FIG. 7, the MusicCDs table may becreated using a CQL version 3 command “CREATE TABLE MusicCDs (UUIDPRIMARY KEY, CD varchar, Artist varchar, Year int, Songs map<varchar,varchar>);” in one embodiment, the dynamic column determination module324 determines that the MusicCDs table includes one or more dynamiccolumns based on the definition including a dynamic column type (i.e. amap). Examples of a dynamic column types may include one or more of aset, a list and a map as defined by CQL version 3. A dynamic column typeis occasionally referred to a column “sub-type” as it is a sub-type ofthe second column type according to one embodiment.

The dynamic column determination module 324 identifies dynamic columnsin the non-relational database table. In one embodiment, there are twocolumn types (e.g. static and dynamic). In one such embodiment, thedynamic column determination module 324 identifies the zero or morecolumns that are not identified as static columns as dynamic columns.

In one embodiment, the dynamic column determination module 324 passesthe identity of dynamic columns to one or more of the optional dynamiccolumn typing module 326 and the table division module 328. In oneembodiment, the dynamic column determination module 324 stores theinformation identifying the dynamic columns in memory 204 (or any othernon-transitory storage medium communicatively accessible). The othermodules of the model generation module 224 including, e.g., the dynamiccolumn typing module 326 and/or the table division module 328, mayretrieve the identity of the dynamic columns by accessing the memory 204(or other non-transitory storage medium).

As mentioned above, in some embodiments, one or more dynamic columns maybe associated with a sub-type. For example, in CQL version 3, dynamiccolumn sub-types may include sets, lists and maps. In some embodiments,the dynamic columns are identified based on sub-type by the optionaldynamic column typing module 326.

The dynamic column typing module 326 includes code and routines foridentifying dynamic columns in a non-relational database based on asub-type. In one embodiment, the dynamic column typing module 326 is aset of instructions executable by the processor 202. In anotherembodiment, the dynamic column typing module 326 is stored in the memory204 and is accessible and executable by the processor 202. In eitherembodiment, the dynamic column typing module 326 is adapted forcooperation and communication with the processor 202, other componentsof the computing device 106/122 and other components of the modelgeneration module 224.

The dynamic column typing module 326 identifies dynamic columns in anon-relational database based on a sub-type. In one embodiment, thedynamic column typing module 326 identifies the dynamic columnsassociated with different sub-types. For example, assume a table iscreated using a CQL version 3 command “CREATE TABLE MusicCDs (UUIDPRIMARY KEY, CD varchar, Artist varchar, Year int, Songs map<varchar,varchar>, BandMemebers list<text>);”. That table may look similar totable 700 where columns 704 are dynamic columns associated with the“Songs” map (e.g. the “Songs” map includes Songs A-B and Songs 1-6 assong title values and the track length values associated with each songtitle), but that table would also include one or more additional dynamiccolumns (not shown) associated with headers in row 706 that include bandmember names. In one embodiment, the dynamic column typing module 326identifies the columns associated with the Song columns 704 asassociated with a first sub-type (i.e. a map) and the columns associatedwith the band members (not shown) as associated with a second sub-type(i.e. a list) differently.

In one embodiment, the dynamic column typing module 326 identifies thedynamic columns associated with the same sub-type similarly. Forexample, assume a table is created using a CQL version 3 command “CREATETABLE MusicCDs (UUID PRIMARY KEY, CD varchar, Artist varchar, Year int,Songs map<varchar, varchar>, SecondMap map<varchar, varchar>);”. Again,that table may look similar to table 700 where columns 704 are dynamiccolumns associated with the “Songs” map, but that table would alsoinclude one or more additional dynamic columns (not shown) associatedwith the “SecondMap” map. In one embodiment, the dynamic column typingmodule 326 identifies the columns associated with the second map (notshown) and the Song columns 704 similarly as both are associated with acommon sub-type (i.e. a map).

In one embodiment, the dynamic column typing module 326 identifiesdynamic columns associated with the same sub-type differently. Forexample, in the example immediately above, the dynamic column typingmodule 326 identifies the Song columns 704 as a first set of dynamiccolumns associated with a first map (i.e. “Songs” map), and identifies asecond set of dynamic columns associated with a second map (i.e.“SecondMap” map).

In one embodiment, the dynamic column typing module 326 passes theidentification based on sub-type to the table division module 328. Inone embodiment, the dynamic column typing module 326 stores theidentification based on sub-type in memory 204 (or any othernon-transitory storage medium communicatively accessible). The othermodules of the model generation module 224 including, e.g., the dynamiccolumn typing module 326, may retrieve the identification based onsub-type by accessing the memory 204 (or other non-transitory storagemedium).

The table division module 328 includes code and routines for dividingthe non-relational database table. In one embodiment, the table divisionmodule 328 is a set of instructions executable by the processor 202. Inanother embodiment, the table division module 328 is stored in thememory 204 and is accessible and executable by the processor 202. Ineither embodiment, the table division module 328 is adapted forcooperation and communication with the processor 202, other componentsof the computing device 106/122 and other components of the modelgeneration module 224.

The table division module 328 divides the non-relational database table.In one embodiment, the table division module 328 divides thenon-relational database table based on the column identifications by thestatic column determination module 322, the dynamic column determinationmodule and, optionally, the dynamic column typing module 326. In oneembodiment, when no dynamic columns are included in the non-relationaldatabase table, the table division module 328 does not perform divisionof the non-relational database table.

In one embodiment, the table division module 328 divides thenon-relational database table “virtually,” i.e., the table divisionmodule 328 does not modify the schema or divide the non-relational tablestored in the non-relational database. Rather, in one embodiment, thetable division module 328 determines how the non-relational database maybe divided into sections that may be represented as separate tables in anormalized, relational model.

In one embodiment, the table division module 328 divides thenon-relational database table based on column type. For example,referring again to table 700 of FIG. 7, in one embodiment, the tabledivision module 328 divides the table 700 into static columns 702 anddynamic columns 704 based on the identification of columns as static ordynamic.

In one embodiment, the table division module 328 further divides thedynamic columns based on sub-type. For example, assume thenon-relational table includes dynamic columns associated with one ormore sets and dynamic columns associated with one or more maps; in oneembodiment, the table division module 328 divides the dynamic columnsinto a set of dynamic columns associated with the one or more sets and aset of dynamic columns associated with the one or more maps.

In one embodiment, the table division module 328 divides among the samesub-type. For example, assume the non-relational table includes columnsassociated with a first map and columns associated with a second map; inone embodiment, the table division module 328 divides the dynamiccolumns into a set of dynamic columns associated with the first map anda set of dynamic columns associated with the second map.

In one embodiment, the table division module 328 passes the dividedtable to the modeling module 330. For example, the table division module328 is communicatively coupled to the modeling module 330 to send thedivided table to the modeling module 330. In another embodiment, thetable division module 328 stores the divided table in memory 204 (or anyother non-transitory storage medium communicatively accessible), and themodeling module 330 may retrieve the divided table by accessing thememory 204 (or other non-transitory storage medium).

The modeling module 330 includes code and routines for generating arelational model of the non-relational database table. In oneembodiment, the modeling module 330 is a set of instructions executableby the processor 202. In another embodiment, the modeling module 330 isstored in the memory 204 and is accessible and executable by theprocessor 202. In either embodiment, the modeling module 330 is adaptedfor cooperation and communication with the processor 202, othercomponents of the computing device 106/122 and other components of themodel generation module 224.

The modeling module 330 generates a relational model of thenon-relational database table. The generation of the relational modeldoes not affect how the data is organized or stored in thenon-relational database. In some embodiments, the relational model doesnot include the data of the non-relational database table. For example,in one embodiment, the relational model includes catalogue informationfor representing one or more relational tables. The tables representedby the catalogue information may occasionally be referred to herein as“virtual tables, “virtual, relational tables” “normalized, virtualrelational tables” or the like. Catalogue information represents arelational database table by describing how at least one of a row, acolumn and a field of the non-relational database table would berepresented as, or mapped to, a relational database table.

For example, FIG. 8 illustrates how the data from the non-relationaldatabase table 700 of FIG. 7 may be reorganized and represented asnormalized, relational database tables 800 and 802 according to oneembodiment. In one embodiment, the relational model for table 700 maynot include the normalized, relational tables 800 and 802 themselves butdescribes how the columns of non-relational table 700 may be reorganizedinto the normalized, relational tables 800 and 802. For example, therelational model includes catalog information describing how the staticcolumns 702 of the non-relational table 700 are mapped to a virtualparent table 802, how the dynamic columns 704 of the non-relationaltable 700 are mapped to the virtual child table 802 by flipping thecolumns on their side (i.e. into rows) and how the rows of the virtualchild table 802 are related to the rows of the virtual parent table 800by a virtual foreign key.

The modeling module 330 generates a relational model of thenon-relational database table based on the table division. In oneembodiment, the modeling module 330 generates catalogue informationrepresenting a separate relational table for each portion of thedivided, non-relational database table. Because the non-relationaldatabase table is represented by more than one relational table in therelational model (assuming the non-relational database table includes atleast on dynamic table), the relational model is occasionally referredto herein as a normalized, relational model.

In one embodiment, the modeling module 330 creates a relational modelthat includes catalogue information for a table based on the one or morestatic columns of the non-relational database. For example, in oneembodiment, the relational model includes catalogue informationrepresenting a relational table that includes all the static columns ofthe non-relational database table. In one embodiment, the relationaltable based on the static columns is the parent table for the relationalmodel and is related to zero or more child tables using foreign keypairing.

In one embodiment, when the non-relational database table includes oneor more dynamic columns, the catalogue information of the relationalmodel represents the dynamic columns in a child table. In oneembodiment, the catalogue information represents all dynamic columns ofthe non-relational database table in a single child table. For example,assume, again, that the non-relational database table uses CQL version 2and that CQL version 2 does not identify sub-types of dynamic columns.In one embodiment, the modeling module 330 generates catalogueinformation representing a single child table that includes (possiblyrearranged) all the dynamic columns of such a non-relational database.

In one embodiment, the catalogue information represents all dynamiccolumns of a common sub-type in the non-relational database table in thesame child table. For example, assume, again, that the non-relationaldatabase table uses CQL version 3 and that CQL version 3 defines lists,sets and maps as sub-types of dynamic columns. In one embodiment, themodeling module 330 generates catalogue information representing a firstchild table including all the dynamic columns that are lists (if any),catalogue information representing a second child table that includesall the dynamic columns that are sets (if any) and catalogue informationthat represents a third child table including all the dynamic columnsthat are maps (if any).

In one embodiment, the catalogue information represents different groupsof dynamic columns having a common sub-type in the non-relationaldatabase table in separate child tables. For example, assume, again,that the non-relational database table uses CQL version 3 and that CQLversion 3 defines lists, sets and maps as sub-types of dynamic columns.Also, assume that the non-relational table includes one or more dynamiccolumns associated with a first map and one or more dynamic columnsassociated with a second map. In one embodiment, the modeling module 330generates catalogue information that represents all the dynamic columnsthat are associated with the first map in a first child table andcatalogue information that represents all the dynamic columns that areassociated with the second map in a second child table.

In one embodiment, the naming convention of the virtual tables in therelational model and the columns therein uses a default namingconvention. In one embodiment, the default naming convention may be usermodifiable.

In one embodiment, the modeling module 330 passes the relational modelto the relational/non-relational translator module 226. For example, themodeling module 330 is communicatively coupled to therelational/non-relational translator module 226 to send the relationalmodel to the relational/non-relational translator module 226. In anotherembodiment, the modeling module 330 stores the relational model inmemory 204 (or any other non-transitory storage medium communicativelyaccessible), and the relational/non-relational translator module 226 mayretrieve the relational model by accessing the memory 204 (or othernon-transitory storage medium).

Example Relational/Non-Relational Translator Module 226

Referring now to FIG. 4, the relational/non-relational translator module226 is shown in more detail according to one embodiment. FIG. 4 is ablock diagram of the relational/non-relational translator module 226included in a computing device 106/122 according to one embodiment.

The relational/non-relational translator module 226 provides translationbetween a relational query language and the non-relational querylanguage of the non-relational database. In one embodiment, therelational/non-relational translator module 226 uses the relationalmodel to provide translation between a relational query language and thenon-relational query language of the non-relational database. Forexample, in one embodiment, the relational/non-relational translatormodule 226 provides translation from SQL to CQL and from CQL to SQL fora query. Such embodiments, may beneficially allow drivers (e.g. ODBC,JDBC, etc. drivers) and applications that are designed to interface withand interact with relational databases to interact with a non-relationaldatabase as if it were a relational database. In other words, therelational/non-relational translator module 226 provides translation sothat the application and/or relational driver “see” the database as arelational database and the non-relational database “sees” onlynon-relational queries.

The query translator module 422 includes code and routines for receivinga relational query, translating the relational query into anon-relational query and sending the non-relational query thenon-relational database. In one embodiment, the query translator module422 is a set of instructions executable by the processor 202. In anotherembodiment, the query translator module 422 is stored in the memory 204and is accessible and executable by the processor 202. In eitherembodiment, the query translator module 422 is adapted for cooperationand communication with the processor 202, other components of thecomputing device 106/122 and other components of the model generationmodule 224.

The query translator module 422 receives a relational query. In oneembodiment, a relational query is a query that uses a relationaldatabase language. For example, in one embodiment, the query translatormodule 422 receives a SQL query from an ODBC or JDBC driver to add,retrieve, modify or manipulate data.

The query translator module 422 obtains the relational model andtranslates the relational query into a non-relational query using therelational model. In one embodiment, the query translator module 422translates the relational query into a non-relational query by mappingany fields, rows, columns, etc. referenced in the relational query(which correspond to fields, rows, columns of one or more the virtualtables of the relational model) to the non-relational table using thecatalogue information and by translating the query into the appropriatenon-relational query and sends the non-relational query to thenon-relational database.

In one embodiment, the query translator module 422 passes thenon-relational query to the non-relational database 120. For example,the query translator module 422 is communicatively coupled to thenon-relational database 120 to send the non-relational query to thenon-relational database 120.

The response translator module 424 includes code and routines forreceiving a non-relational response from the non-relational database,translating the non-relational response into a relational response andsending the relational response. In one embodiment, the responsetranslator module 424 is a set of instructions executable by theprocessor 202. In another embodiment, the response translator module 424is stored in the memory 204 and is accessible and executable by theprocessor 202. In either embodiment, the response translator module 424is adapted for cooperation and communication with the processor 202,other components of the computing device 106/122 and other components ofthe model generation module 224.

The response translator module 424 receives a non-relational response.In one embodiment, a non-relational response is a response in anon-relational database language. For example, in one embodiment, theresponse translator module 424 receives a CQL response from thenon-relational database to a CQL query.

The response translator module 424 obtains the relational model andtranslates the non-relational response into a relational response usingthe relational model. In one embodiment, the response translator module424 uses the catalogue information of the relational model to map anyfields, rows, columns, etc. of the non-relational response tocorresponding fields, rows, columns, etc. of the one or more the virtualrelational tables and by translating the response into the appropriaterelational response and sends the relational response to the requestingdriver and/or application.

In one embodiment, the response translator module 424 passes therelational response to the requesting driver and/or application. Forexample, the response translator module 424 is communicatively coupledto the requesting driver and/or application to send the relationalresponse to the requesting driver and/or application.

Example Methods

FIG. 5 depicts method 500 performed by the system described above inreference to FIGS. 1-3. The method 500 begins at block 502. At block502, the model generation module 224 identifies a non-relational tableto be modeled as one or more normalized, relational tables. At block504, the static column determination module 322 identifies staticcolumns in the non-relational table identified at block 502. At block506, the dynamic column determination module 324 identifies dynamiccolumns in the non-relational table.

Depending on the embodiment, the non-relational database may support aplurality of different dynamic column types. In embodiments that do notsupport different dynamic column types, the method may continue at block510. In some embodiments that support different dynamic column types,the method continues at block 508 before proceeding to block 510. Atblock 508, the optional dynamic column typing module 326 identifiesdynamic columns based on sub-type. At block 510, the table divisionmodule 328 virtually divides the non-relational table based on columntype (which may include sub-type depending on the embodiment). At block512, the modeling module 330 generates a normalized, virtual relationalmodel.

FIG. 6 depicts method 600 performed by the system described above inreference to FIGS. 1-4. The method 600 begins at block 500. At block500, the model generation module 224 generates a normalized, virtualrelational model of a non-relational database, e.g., using method 500described above. At block 604, the query translator module 422 receivesa relational query. At block 606, the query translator module 422retrieves the normalized, virtual relational model. At block 608, thequery translator module 422 translates the relational query into anon-relational query based on the normalized, virtual relational modelretrieved at block 606. At block 610, the query translator module 422sends the non-relational query to the non-relational database 120. Atblock 612, the response translator module 424 receives a response fromthe non-relational database 120. At block 614, the response translatormodule 424 translates the non-relational response received at block 612into a relational response based on the normalized, virtual relationalmodel. At block 616, the response translator module 424 sends therelational response.

In some embodiments, after the relational response is sent at block 616,blocks 604-616 may be repeated for subsequent queries before ending theprocess (e.g. before disconnecting from the non-relational database). Inother words, in some embodiments, the normalized, virtual relationalmodel need not be generated (i.e. block 500 is not necessarily repeated)for each query. For example, depending on the embodiment, thenormalized, virtual relational model is generated (e.g. block 500 isperformed) responsive to one or more of connecting to the non-relationaldatabase, a schema modifying update (e.g. addition/removal of a columnin the non-relational database) and the expiration of a period and thegenerated relational model may be used repeatedly in the translation ofmultiple queries and responses.

In the above description, for purposes of explanation, numerous specificdetails are set forth in order to provide a thorough understanding ofthe present disclosure. However, it should be understood that thetechnology described herein can be practiced without these specificdetails. Further, various systems, devices, and structures are shown inblock diagram form in order to avoid obscuring the description. Forinstance, various implementations are described as having particularhardware, software, and user interfaces. However, the present disclosureapplies to any type of computing device that can receive data andcommands, and to any peripheral devices providing services.

Reference in the specification to “one embodiment” or “an embodiment”means that a particular feature, structure, or characteristic describedin connection with the embodiment is included in at least oneembodiment. The appearances of the phrase “in one embodiment” in variousplaces in the specification are not necessarily all referring to thesame embodiment.

In some instances, various implementations may be presented herein interms of algorithms and symbolic representations of operations on databits within a computer memory. An algorithm is here, and generally,conceived to be a self-consistent set of operations leading to a desiredresult. The operations are those requiring physical manipulations ofphysical quantities. Usually, though not necessarily, these quantitiestake the form of electrical or magnetic signals capable of being stored,transferred, combined, compared, and otherwise manipulated. It hasproven convenient at times, principally for reasons of common usage, torefer to these signals as bits, values, elements, symbols, characters,terms, numbers, or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the following discussion,it is appreciated that throughout this disclosure, discussions utilizingterms including “processing,” “computing,” “calculating,” “determining,”“displaying,” or the like, refer to the action and processes of acomputer system, or similar electronic computing device, thatmanipulates and transforms data represented as physical (electronic)quantities within the computer system's registers and memories intoother data similarly represented as physical quantities within thecomputer system memories or registers or other such information storage,transmission or display devices.

Various implementations described herein may relate to an apparatus forperforming the operations herein. This apparatus may be speciallyconstructed for the required purposes, or it may comprise ageneral-purpose computer selectively activated or reconfigured by acomputer program stored in the computer. Such a computer program may bestored in a computer readable storage medium, including, but is notlimited to, any type of disk including floppy disks, optical disks,CD-ROMs, and magnetic disks, read-only memories (ROMs), random accessmemories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, flashmemories including USB keys with non-volatile memory or any type ofmedia suitable for storing electronic instructions, each coupled to acomputer system bus.

The technology described herein can take the form of an entirelyhardware implementation, an entirely software implementation, orimplementations containing both hardware and software elements. Forinstance, the technology may be implemented in software, which includesbut is not limited to firmware, resident software, microcode, etc.

Furthermore, the technology can take the form of a computer programproduct accessible from a computer-usable or computer-readable mediumproviding program code for use by or in connection with a computer orany instruction execution system. For the purposes of this description,a computer-usable or computer readable medium can be any non-transitorystorage apparatus that can contain, store, communicate, propagate, ortransport the program for use by or in connection with the instructionexecution system, apparatus, or device.

A data processing system suitable for storing and/or executing programcode may include at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements can includelocal memory employed during actual execution of the program code, bulkstorage, and cache memories that provide temporary storage of at leastsome program code in order to reduce the number of times code must beretrieved from bulk storage during execution. Input/output or I/Odevices (including but not limited to keyboards, displays, pointingdevices, etc.) can be coupled to the system either directly or throughintervening I/O controllers.

Network adapters may also be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems,storage devices, remote printers, etc., through intervening privateand/or public networks. Wireless (e.g., Wi-Fi™) transceivers, Ethernetadapters, and modems, are just a few examples of network adapters. Theprivate and public networks may have any number of configurations and/ortopologies. Data may be transmitted between these devices via thenetworks using a variety of different communication protocols including,for example, various Internet layer, transport layer, or applicationlayer protocols. For example, data may be transmitted via the networksusing transmission control protocol/Internet protocol (TCP/IP), userdatagram protocol (UDP), transmission control protocol (TCP), hypertexttransfer protocol (HTTP), secure hypertext transfer protocol (HTTPS),dynamic adaptive streaming over HTTP (DASH), real-time streamingprotocol (RTSP), real-time transport protocol (RTP) and the real-timetransport control protocol (RTCP), voice over Internet protocol (VOIP),file transfer protocol (FTP), WebSocket (WS), wireless access protocol(WAP), various messaging protocols (SMS, MMS, XMS, IMAP, SMTP, POP,WebDAV, etc.), or other known protocols.

Finally, the structure, algorithms, and/or interfaces presented hereinare not inherently related to any particular computer or otherapparatus. Various general-purpose systems may be used with programs inaccordance with the teachings herein, or it may prove convenient toconstruct more specialized apparatus to perform the required methodblocks. The required structure for a variety of these systems willappear from the description above. In addition, the specification is notdescribed with reference to any particular programming language. It willbe appreciated that a variety of programming languages may be used toimplement the teachings of the specification as described herein.

The foregoing description has been presented for the purposes ofillustration and description. It is not intended to be exhaustive or tolimit the specification to the precise form disclosed. Manymodifications and variations are possible in light of the aboveteaching. It is intended that the scope of the disclosure be limited notby this detailed description, but rather by the claims of thisapplication. As will be understood by those familiar with the art, thespecification may be embodied in other specific forms without departingfrom the spirit or essential characteristics thereof. Likewise, theparticular naming and division of the modules, routines, features,attributes, methodologies and other aspects are not mandatory orsignificant, and the mechanisms that implement the specification or itsfeatures may have different names, divisions and/or formats.

Furthermore, the modules, routines, features, attributes, methodologiesand other aspects of the disclosure can be implemented as software,hardware, firmware, or any combination of the foregoing. Also, wherevera component, an example of which is a module, of the specification isimplemented as software, the component can be implemented as astandalone program, as part of a larger program, as a plurality ofseparate programs, as a statically or dynamically linked library, as akernel loadable module, as a device driver, and/or in every and anyother way known now or in the future. Additionally, the disclosure is inno way limited to implementation in any specific programming language,or for any specific operating system or environment. Accordingly, thedisclosure is intended to be illustrative, but not limiting, of thescope of the subject matter set forth in the following claims.

What is claimed is:
 1. A computer-implemented method comprising:dividing, using one or more processors, a column-oriented,non-relational database based on column type, the column-oriented,non-relational database including a first column having a first type anda second column having a second type; and generating, using the one ormore processors, a relational model of the column-oriented,non-relational database based on the division of the column-oriented,non-relational database, wherein the relational model includes cataloginformation representing a parent table including the first columnhaving the first type and catalogue information representing a childtable including the second column having the second type, wherein theparent table and child table are both represented as relational tables.2. The computer-implemented method of claim 1, wherein the division ofthe column-oriented, non-relational database based on column type is avirtual division.
 3. The computer-implemented method of claim 1, whereinthe relational model of the column-oriented, non-relational database isa normalized relational model.
 4. The computer-implemented method ofclaim 3, wherein one or more columns having the second type, includingthe second column, are represented as a separate child table in therelational model.
 5. The computer-implemented method of claim 1, whereinthe catalogue information representing the parent table includes eachcolumn in the column-oriented, non-relational database having the firsttype.
 6. The computer-implemented method of claim 1, wherein thecolumn-oriented, non-relational database is a Cassandra database anduses a version of Cassandra Query Language.
 7. The computer-implementedmethod of claim 1, wherein the column-oriented, non-relational databasetable includes a plurality of columns having the second type and therelation model includes catalogue information representing two or morechild tables including a first child table including a first set of theplurality of columns having the second type and a second child tableincluding a second set of the plurality of columns having the secondtype.
 8. The computer-implemented method of claim 1, further comprising:receiving a relational query from a driver; retrieving the relationalmodel of the column-oriented, non-relational database; mapping, usingthe relational model of the column-oriented, non-relational database,the relational query to associated fields and query language for thecolumn-oriented, non-relational database; generating a non-relationalquery; and sending the non-relational query to the column-oriented,non-relational database.
 9. The computer-implemented method of claim 8,wherein the driver is one of a Java Database Connectivity driver and anOpen Database Connectivity driver.
 10. The computer-implemented methodof claim 1, further comprising: receiving a non-relational response to aquery from the column-oriented, non-relational database; retrieving therelational model of the column-oriented, non-relational database;mapping, using the relational model of the column-oriented,non-relational database, the non-relational response to associatedfields and query language for a driver that uses a relational querylanguage; generating a relational response; and sending the relationalresponse to the driver that uses the relational language.
 11. Thecomputer-implemented method of claim 10, wherein the driver that usesthe relational language is one of a Java Database Connectivity driverand an Open Database Connectivity driver.
 12. A system comprising: aprocessor; a memory storing instructions that, when executed, cause thesystem to: divide a column-oriented, non-relational database based oncolumn type, the column-oriented, non-relational database including afirst column having a first type and a second column having a secondtype; and generate a relational model of the column-oriented,non-relational database based on the division of the column-oriented,non-relational database, wherein the relational model includes cataloginformation representing a parent table including the first columnhaving the first type and catalogue information representing a childtable including the second column having the second type, wherein theparent table and child table are both represented as relational tables.13. The system of claim 12, wherein the division of the column-oriented,non-relational database based on column type is a virtual division. 14.The system of claim 12, wherein the catalogue information representingthe parent table includes each column in the column-oriented,non-relational database having the first type.
 15. The system of claim12, wherein the column-oriented, non-relational database is a Cassandradatabase and uses a version of Cassandra Query Language.
 16. The systemof claim 12, wherein one or more identified columns having the secondtype, including the second column, are represented as a separate childtable in the relational model, wherein the relational model is anormalized, relational model.
 17. The system of claim 12, wherein thecolumn-oriented, non-relational database table includes a plurality ofcolumns having the second type and the relation model includes catalogueinformation representing at least two child tables including a firstchild table including a first set of the plurality of columns having thesecond type and a second child table including a second set of theplurality of columns having the second type.
 18. The system of claim 12,the memory further storing instructions that, when executed, cause thesystem to: receive a relational query from a driver; retrieve therelational model of the column-oriented, non-relational database; map,using the relational model of the column-oriented, non-relationaldatabase, the relational query to associated fields and query languagefor the column-oriented, non-relational database; generate anon-relational query; and send the non-relational query to thecolumn-oriented, non-relational database.
 19. The system of claim 12,the memory further storing instructions that, when executed, cause thesystem to: receive a non-relational response to a query from thecolumn-oriented, non-relational database; retrieve the relational modelof the column-oriented, non-relational database; map, using therelational model of the column-oriented, non-relational database, thenon-relational response to associated fields and query language for adriver that uses a relational query language; generate a relationalresponse; and send the relational response to the driver that uses therelational language.
 20. The system of claim 12, wherein the systemincludes one of a Java Database Connectivity driver and an Open DatabaseConnectivity driver.